AI model accurately localizes optical neuronal cells
Deep learning method could improve diagnosis of neuron-damaging eye and brain diseases
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Irina Grigorescu is a PhD student contributor to Physics World, working in the Perinatal Imaging & Health Department at King's College London. Her research uses magnetic resonance imaging and deep learning techniques to characterize developmental outcomes in babies born preterm. In her spare time, she volunteers for STEM outreach activities, and likes reading science fiction and popular science novels.
Deep learning method could improve diagnosis of neuron-damaging eye and brain diseases
An artificial intelligence velocimetry framework combined with a microfluidic chip quantifies blood flow characteristics to help understand vascular disease
Diffusion-weighted MR imaging and machine learning techniques can accurately distinguish between common types of paediatric brain tumours
A deep-learning model trained to detect occlusions of large vessels has the potential to speed up clinical diagnosis
Human anatomical models with simulated coronavirus lung pathologies have could optimize CT and radiography acquisitions to effectively screen and manage COVID-19 patients
Superconducting single-photon detector allows acquisition of high-fidelity optical coherence tomography images at very low light power levels
A novel diffusion MRI-based method paves the way towards non-invasive measurements of axonal sizes
Artificial intelligence-derived image features predict prostate cancer recurrence with high accuracy
Giving premature infants daily music therapy during intensive care stays increased structural maturation of their brain's auditory and emotional processing pathways
Just one hour of brain–computer interface use led to clear changes in neuronal patterns, raising hopes of a potential new therapy for stroke victims
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